ANALYSIS OF MULTIVARIATE SURVIVAL DATA HOUGAARD PDF

Category: Survival Supplies The isolated local recurrence in a patient previously treated for early-stage invasive breast cancer presents a unique challenge to the oncologist. The clinical significance of an isolated local recurrence as a first event after treatment of early-stage invasive breast cancer, and its impact on survival, remains controversial. The purpose of this review is to analyze the incidence and risk factors for local recurrence after initial treatment of invasive breast cancer. Studies using multivariate analysis to account for other known prognostic factors have shown that age may not be an independent predictor of locoregional recurrence. According to a statistical model reported by Iyer et al[34], inaccuracy of the staging of a patient with? In a series of node-positive postmenopausal women treated by mastectomy and tamoxifen Nolvadex , Fisher et al[43] found that a positive margin was a significant predictor of locoregional recurrence on multivariate analysis.

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I think that this book will be useful to statisticians who are dealing with modeling multivariate failure time data in their applied work. In addition it is a good reference to the technical literature available in this field.

His insights into the nature of dependence extend far beyond survival analysis and touch some of the most fundamental aspects of our discipline. Adequate up-to-date references are provided for interested readers to follow up if required.

The level of mathematical detail is nice I believe this to be the first book on multivariate survival. Anyone considering writing the second book has a hard act to follow - this sets a very high standard and is recommended for all statisticians with an interest in survival analysis techniques.

Unlike other books on survival, most of which have just one or two chapters dealing with multivariate material, this book is the first comprehensive treatment fully focusing on multivariate survival data This book is a long-awaited work that summarizes the state of the art of multivariate survival analysis and provides a valuable reference. The aim of the book is very clearly laid down. The exercises at the end of each chapter makes it more useful The chapter summary and bibliographic comments are also very useful.

The computational aspects It should This book is without any doubt an indispensable reading for both theoretical and practical statisticians.

In fact, this book will be most interesting for professional statisticians advancing to this field. Every chapter contains a set of exercises suitable to practice The book is a pleasure to read. Every chapter contains an extensive summary which is very helpful In my opinion the author has succeeded in completing a valuable monograph on multivariate survival analysis. Throughout the book theoretical developments are extensively exemplified by real-life examples and computational aspects are dealt with as well.

A commendable feature is that each of the chapters starts with an intuitional introduction and ends with a brief summary section, bibliographic comments and exercises. One of the most useful aspects of this book, in my opinion, is the extensive use made of practical examples.

There are exercises at the end of each chapter. The organization of the book, and the good use of cross referencing, mean that it can be read in varying degrees of depth. This book should prove an informative extension to the literature on survival analysis.

DEQ-9200 MANUAL PDF

Analysis of Multivariate Survival Data

Survival data or more general time-to-event data occur in many areas, including medicine, biology, engineering, economics, and demography, but previously standard methods have requested that all time variables are univariate and independent. This book extends the field by allowing for multivariate times. Applications where such data appear are survival of twins, survival of married couples and families, time to failure of right and left kidney for diabetic patients, life history data with time to outbreak of disease, complications and death, recurrent episodes of diseases and cross-over studies with time responses. As the field is rather new, the concepts and the possible types of data are described in detail and basic aspects of how dependence can appear in such data is discussed. Four different approaches to the analysis of such data are presented. The multi-state models where a life history is described as the subject moving from state to state is the most classical approach. The Markov models make up an important special case, but it is also described how easily more general models are set up and analyzed.

KP THAKUR ENGLISH GRAMMAR PDF

About this book Introduction Survival data or more general time-to-event data occur in many areas, including medicine, biology, engineering, economics, and demography, but previously standard methods have requested that all time variables are univariate and independent. This book extends the field by allowing for multivariate times. Applications where such data appear are survival of twins, survival of married couples and families, time to failure of right and left kidney for diabetic patients, life history data with time to outbreak of disease, complications and death, recurrent episodes of diseases and cross-over studies with time responses. As the field is rather new, the concepts and the possible types of data are described in detail and basic aspects of how dependence can appear in such data is discussed. Four different approaches to the analysis of such data are presented. The multi-state models where a life history is described as the subject moving from state to state is the most classical approach.

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